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Chapter Twelve - Bovine tuberculosis in badgers: sociality, infection and demography in a social mammal

from Part II - Understanding between-host processes

Published online by Cambridge University Press:  28 October 2019

By
Jenni L. McDonald ,
Richard J. Delahay  and
Robbie A. McDonald
Edited by
Kenneth Wilson ,
Andy Fenton  and
Dan Tompkins
Kenneth Wilson
Affiliation:
Lancaster University
Andy Fenton
Affiliation:
University of Liverpool
Dan Tompkins
Affiliation:
Predator Free 2050 Ltd
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Summary

Badgers are an important reservoir of bovine TB in the UK. We discuss how the combination of individual epidemiological data, tracking studies and modelling frameworks enabled exploration of host–pathogen theories in relation to badger life history and disease ecology, focusing on heterogeneity in host susceptibility and infectiousness, two components of the superspreader phenotype. Studies pairing empirical data with modelling approaches suggest sex differences are underpinned by immunological mechanisms. We discuss how studies have moved away from the simplistic assumption of randomly mixing homogeneous populations towards recognition of heterogeneity in host association patterns at group, class and individual levels. Interactions between individuals are non-random with high within-group contacts and lower between-group contact rates. Contact heterogeneity is fundamental to understanding what drives/restricts the spatial spread of disease through a population. We explore a demographic perspective on disease ecology, showing how demographic intricacies provide further understanding of the mechanisms underpinning persistence of infected badger populations. The understanding gained from longitudinal studies of host–pathogen field systems is important ecological and epidemiological theory development and informs evidence-based disease control strategies’ development.

Keywords

Woodchester ParkMeles melesMycobacterium bovissusceptibilityheterogeneitysuperspreaderepidemiologycontact ratescompensatory recruitment
Type
Chapter
Information
Wildlife Disease Ecology
Linking Theory to Data and Application
 , pp. 342 - 367
Publisher: Cambridge University Press
Print publication year: 2019

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